E-GEOD-10402 - A 50-Gene Predictor of Recurrence as a Guide to Therapy in Early-Stage Colon Cancer.

Status
Submitted on 6 February 2008, released on 15 May 2010, last updated on 2 May 2014
Organism
Homo sapiens
Samples (146)
Array (1)
Protocols (7)
Description
Gene expression profiles reflect unique aspects of individual biologic phenotypes and may characterize the heterogeneity of solid tumors. Using previously-described methodologies that employ DNA microarray data, a 50-gene expression profile (metagene) that predicts risk of recurrence in early stage colon carcinoma was identified. This analysis used an initial discovery cohort of 52 patients. The performance of the 50-gene predictor was evaluated in an independent validation cohort of 73 patients. Using a connectivity map analysis of the 50-gene model, we identified candidate agents and then tested the in vitro efficacy of these compounds in colon cancer cell lines. 73 samples that had patient recurrence data with stage information were used in the analysis. Keywords: Disease state analysis A total of 73 samples were spotted on microarray slides. No replicates are included in the study.
Experiment type
transcription profiling by array 
Contacts
Chaitanya Ramanuj Acharya <c.acharya@duke.edu>, Anil Potti, Chaitanya R Acharya, David S Hsu, Geoffrey S Ginsburg, Joseph R Nevins, Katherine S Garman, Kelli S Walters, Marian Grade, Sayan Mukerjee, Shivani Sud, Thomas Ried, William T Barry
Citation
A genomic approach to colon cancer risk stratification yields biologic insights into therapeutic opportunities. Garman KS, Acharya CR, Edelman E, Grade M, Gaedcke J, Sud S, Barry W, Diehl AM, Provenzale D, Ginsburg GS, Ghadimi BM, Ried T, Nevins JR, Mukherjee S, Hsu D, Potti A.
MIAME
PlatformsProtocolsFactorsProcessedRaw
Files
Investigation descriptionE-GEOD-10402.idf.txt
Sample and data relationshipE-GEOD-10402.sdrf.txt
Raw data (2)E-GEOD-10402.raw.1.zip, E-GEOD-10402.raw.2.zip
Processed data (1)E-GEOD-10402.processed.1.zip
Array designA-GEOD-6465.adf.txt
R ExpressionSetE-GEOD-10402.eSet.r
Links